Apparatus for processing medical image and method of processing medical image thereof

ABSTRACT

An apparatus for processing a medical image includes an image processor including a plurality of processors, the plurality of processors configured to reconstruct a cross-sectional image of an object by performing a first operation having a first priority and a second operation having a second priority that is lower than the first priority, and a controller configured to monitor whether a malfunction occurs among the plurality of processors, and configured to assign, to at least one of the plurality of processors, at least one of the first operation and the second operation to be performed, based on a result of monitoring of the plurality of processors.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.14/862,363 filed on Sep. 23, 2015 which claims priority from KoreanPatent Application No. 10-2014-0127190, filed on Sep. 23, 2014, andKorean Patent Application No. 10-2015-0073926, filed on May 27, 2015, inthe Korean Intellectual Property Office, the disclosures of which areincorporated herein in their entireties by reference.

BACKGROUND 1. Field

Apparatuses and methods consistent with exemplary embodiments relate toan apparatus for processing a medical image and a method of processing amedical image thereof, and more particularly, to a computed tomography(CT) image processing apparatus for obtaining a cross-sectional imagereconstructed by using a plurality of graphics processor units (GPUs)and a method of processing a CT image thereof.

2. Description of the Related Art

Computed tomography (CT) image processing apparatuses are used to obtainan image of the internal structure of an object. The CT image processingapparatuses are non-invasive and enable users to view an image of anobject after capturing and processing the image including structuraldetails of a body, the internal organs, the flow of body fluids, etc.Users, including doctors, may diagnose medical conditions and diseasesby using images generated by the CT image processing apparatuses.

A CT image processing apparatus needs to quickly process a massiveamount of data during a reconstruction process in which the CT imageprocessing apparatus obtains a cross-sectional image based on dataacquired through CT imaging. Therefore, a CT image processing apparatusexecutes a task of processing an image, which involves a massive amountof data, by using a field programmable gate array (FPGA) and amulti-central processing unit (Multi-CPU).

In addition, diagnoses using CT-imaging technology are frequently usedin emergency situations, compared to types of diagnoses using othermedical equipment. Therefore, there may be circumstances in which usersneed to monitor the medical conditions of a patient in real time whilethe CT imaging is being performed. Therefore, methods are introduced toreconstruct the cross-sectional images by using graphics processor units(GPUs) which have more enhanced processing capacities than conventionalcentral processing units (CPUs).

Furthermore, the CT image processing apparatuses may boost efficiency byusing a Multi-GPU architecture, which includes a plurality of GPUs, whenreconstructing a cross-sectional image, to further boost imagereconstruction speed.

However, the plurality of GPUs included as part of the Multi-GPUarchitecture perform the task of an image processing interdependently.Therefore, when the GPUs are used in the reconstruction of thecross-sectional image, if at least one of the plurality of the GPUsmalfunctions, the CT image processing apparatuses may have difficulty inreconstructing an intended cross-sectional image.

SUMMARY

One or more exemplary embodiments provide an apparatus for obtaining amedical image, which may obtain a cross-sectional image of an object ata normal pace even when there is at least one malfunctioning graphicsprocessor unit (GPU) among a plurality of GPUs that are used toreconstruct the cross-sectional image of the object by using dataobtained from computed tomography (CT) imaging.

One or more exemplary embodiments provide an apparatus for obtaining amedical image, which may efficiently reconstruct various types ofcross-sectional images based on priorities in executing thereconstruction of various types of cross-sectional images by using theplurality of GPUs.

One or more exemplary embodiments provide an apparatus for obtaining amedical image, which may efficiently assign a task of reconstructingvarious types of cross-sectional images based on priorities according tovarious types of reconstructing operation of cross-sectional images,even when there is at least one malfunctioning GPU among a plurality ofGPUs.

Additional aspects will be set forth in part in the description whichfollows and, in part, will be apparent from the description, or may belearned by practice of the presented exemplary embodiments.

According to an aspect of an exemplary embodiment, provided is anapparatus for processing a medical image, the apparatus including: animage processor including a plurality of processors, the plurality ofprocessors configured to reconstruct a cross-sectional image of anobject by performing a first operation having a first priority and asecond operation having a second priority that is lower than the firstpriority; and a controller configured to monitor whether a malfunctionoccurs among the plurality of processors, and configured to assign, toat least one of the plurality of processors, at least one of the firstoperation and the second operation to be performed, based on a result ofmonitoring of the plurality of processors.

The controller may be configured to assign the at least one of the firstoperation and the second operation to the at least one of the pluralityof processors, such that the first operation is firstly performed.

When the controller may be configured to detect a malfunction in aprocessor based on the result of the monitoring, the controller isconfigured to assign the at least one of the first operation and thesecond operation to at least one among the plurality of processorsexcept for the processor in which the malfunction is detected.

The apparatus may further include a displayer configured to display thereconstructed cross-sectional image.

The plurality of processors may be configured to reconstruct thecross-sectional image of the object based on computed tomography (CT)data obtained by performing a CT imaging on the object.

The displayer may be configured to display a first cross-sectional imagegenerated by using the first operation while the CT imaging is beingperformed on the object.

The displayer may be configured to display a second cross-sectionalimage generated by the second operation, the second operation beingperformed on the object after the CT imaging of the object is completed.

The second operation may include a scan reconstruction, and the scanreconstruction is performed by reconstructing the second cross-sectionalimage by using the CT data in a manner different from reconstructing thefirst cross-sectional image by using the first operation.

The second operation may further include post reconstruction by whichthe second cross-sectional image of the object is generated based on atleast one of the CT data and the first cross-sectional image.

The controller may be configured to assign the second operation to theat least one of the plurality of processors, and configured to controlthe at least one of the plurality of processors to perform the postreconstruction after performing the scan reconstruction.

The controller may be configured to assign the first operation to agreater number of a processor than a number of a processor to which thesecond operation is assigned.

The controller may be configured to assign the at least one of the firstoperation and the second operation to each of the plurality ofprocessors based on a total number of the plurality of processors and anumber of a processor in which the malfunction is detected.

The controller may be configured to maintain a number of a processor towhich the first operation is assigned regardless of whether themalfunction occurs among the plurality of processors.

The controller may be configured to maintain a speed at which thecross-sectional image of the object is generated by the first operationregardless of whether the malfunction occurs among the plurality ofprocessors.

The apparatus may further include an input unit configured to receive aninput indicating the second operation, wherein the image processor isconfigured to determine an image reconstruction method of the secondoperation, based on the input.

According to an aspect of an exemplary embodiment, provided is a methodof processing a medical image, the method including: detecting whether amalfunction occurs among a plurality of processors, the plurality ofprocessors configured to reconstruct a cross-sectional image of anobject, and based on a result of the detecting, assigning, to at leastone of the plurality of processors, at least one of a first operationhaving a first priority and a second operation having a second prioritythat is lower than the first priority, the first operation and thesecond operation being performed to reconstruct the cross-sectionalimage of the object.

The assigning may include assigning the at least one of the firstoperation and the second operation to the at least one of the pluralityof processors, such that the first operation is firstly performed.

The assigning may include assigning, when a malfunction is detected in aprocessor based on the result of the detecting, the at least one of thefirst operation and the second operation to at least one among theplurality of processors except for the processor in which themalfunction is detected.

The method may further include displaying the reconstructedcross-sectional image.

The plurality of processors may be configured to reconstruct thecross-sectional image of the object based on CT data obtained through aCT imaging of the object.

The displaying may include displaying a first cross-sectional imagegenerated by the first operation while the CT imaging is being performedon the object.

The displaying may include displaying a second cross-sectional imageobtained through the second operation, the second operation beingperformed on the object after the CT imaging is completed.

The second operation may include scan reconstruction, and the scanreconstruction is performed by reconstructing the second cross-sectionalimage by using the CT data in a manner different from reconstructing thefirst cross-sectional image by using the first operation.

The second operation may further include post reconstruction by whichthe second cross-sectional image of the object is generated based on atleast one of the CT data and the first cross-sectional image.

When the assigning includes assigning the second operation to the atleast one of the plurality of processors, the at least one of theplurality of processors may be configured to perform the postreconstruction after the scan reconstruction is completed.

A number of a processor assigned to the first operation may be greaterthan a number of a processor assigned to the second operation.

The assigning may include assigning the at least one of the firstoperation and the second operation to each of the plurality ofprocessors based on a total number of the plurality of processors and anumber of a processor in which the malfunction is detected.

A number of a processor assigned to the first operation may bemaintained regardless of whether the malfunction occurs among theplurality of processors.

A speed at which the cross-sectional image of the object is generated bythe first operation may be maintained regardless of whether themalfunction occurs among the plurality of processors.

The method may further include receiving an input indicating the secondoperation, and determining an image reconstruction method of the secondoperation, based on the input.

According to an aspect of an exemplary embodiment, provided is atomography apparatus including: a data acquirer configured to acquire animage of an object by performing a tomography scan on the object; and animage processor including a plurality of processors and configured toreconstruct a cross-section image of the object by performing two ormore different reconstruction operations on the object, wherein a numberof a processor that performs a certain reconstruction operation isdetermined based on a total number of the plurality of processors and anumber of a processor in which a malfunction is detected.

The two or more different reconstruction operations may differ from eachother with respect to at least one from among an image reconstructionmethod, an image processing method, and an image displaying method.

A number of a processor that performs a first reconstruction, among theplurality of processors except for the processor in which themalfunction is detected, may be greater than a number of a processorthat performs a second reconstruction operation.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or other aspects will be more apparent by describingcertain example embodiments with reference to the accompanying drawingsin which:

FIG. 1 schematically illustrates a computed tomography (CT) systemaccording to an exemplary embodiment;

FIG. 2 is a view illustrating a structure of a CT system according to anexemplary embodiment;

FIG. 3A, FIG. 3B, and FIG. 3C are views illustrating a method ofprocessing a cross-sectional image according to exemplary embodiments;

FIG. 4 is a block diagram of a CT image processing apparatus accordingto an exemplary embodiment;

FIG. 5 is a block diagram of a CT image processing apparatus accordingto another exemplary embodiment;

FIG. 6 is a flowchart of a method of processing a CT image according toan exemplary embodiment;

FIG. 7, FIG. 8A, FIG. 8B, FIG. 9, and FIG. 10 are views illustratingexamples of assigning an operation of image reconstruction based onpriorities in a method of processing a CT image according to exemplaryembodiments;

FIG. 11A and FIG. 11B are sequence diagrams of a method of processing aCT image by a CT image processing apparatus according to an exemplaryembodiment;

FIG. 12A and FIG. 12B are sequence diagrams of a method of processing aCT image by a CT image processing apparatus according to anotherexemplary embodiment; and

FIG. 13A, FIG. 13B, and FIG. 13C are views illustrating a user interfacescreen which indicates an operation status of each of a plurality ofgraphics processor units (GPUs) of an apparatus for processing a medicalimage.

DETAILED DESCRIPTION

Reference will now be made in detail to exemplary embodiments, examplesof which are illustrated in the accompanying drawings, wherein likereference numerals refer to like elements throughout. In this regard,the present exemplary embodiments may have different forms and shouldnot be construed as being limited to the descriptions set forth herein.Accordingly, the exemplary embodiments are merely described below, byreferring to the figures, to explain aspects of the present description.In the following description, well-known functions or constructions arenot described in detail so as not to obscure the exemplary embodimentswith unnecessary detail.

One or more exemplary embodiments and methods of accomplishing the samemay be understood more readily by reference to the following detaileddescription of the exemplary embodiments and the accompanying drawings.In this regard, the exemplary embodiments may have different forms andshould not be construed as being limited to the descriptions set forthherein. Rather, these embodiments are provided so that this disclosurewill be thorough and complete and will fully convey the concept of theexemplary embodiments to one of ordinary skill in the art, and thedisclosure will only be defined by the appended claims. Like referencenumerals refer to like elements throughout the specification.

Hereinafter, the terms used in the specification will be brieflydefined, and the exemplary embodiments will be described in detail.

All terms including descriptive or technical terms which are used hereinshould be construed as having meanings that are obvious to one ofordinary skill in the art. However, the terms may have differentmeanings according to the intention of one of ordinary skill in the art,precedent cases, or the appearance of new technologies. Also, some termsmay be arbitrarily selected by the applicant, and in this case, themeaning of the selected terms will be described in detail in thedetailed description of the disclosure. Thus, the terms used herein haveto be defined based on the meaning of the terms together with thedescription throughout the specification.

When a part “includes” or “comprises” an element, unless there is aparticular description contrary thereto, the part can further includeother elements, not excluding the other elements. Also, the term “unit”in the exemplary embodiments means a software component or hardwarecomponent such as a field-programmable gate array (FPGA) or anapplication-specific integrated circuit (ASIC), and performs a specificfunction. However, the term “unit” is not limited to software orhardware. The “unit” may be formed to be in an addressable storagemedium, or may be formed to operate one or more processors. Thus, forexample, the term “unit” may refer to components such as softwarecomponents, object-oriented software components, class components, andtask components, and may include processes, functions, attributes,procedures, subroutines, segments of program code, drivers, firmware,micro codes, circuits, data, a database, data structures, tables,arrays, or variables. A function provided by the components and “units”may be associated with the smaller number of components and “units”, ormay be divided into additional components and “units”.

Throughout the specification, an “image” may mean multi-dimensional dataformed of discrete image elements, e.g., pixels in a two-dimensional(2D) image and voxels in a three-dimensional (3D) image. For example,the image may include a medical image of an object which is captured bya computed tomography (CT) imaging apparatus.

Throughout the specification, a “CT image” may mean an image generatedby synthesizing a plurality of X-ray images that are obtained byphotographing an object while a computed tomography (CT) imagingapparatus rotates around at least one axis with respect to the object.

Furthermore, in the present specification, an “object” may be a human,an animal, or a part of a human or animal. For example, the object maybe an organ (e.g., the liver, heart, womb, brain, breast, or abdomen), ablood vessel, or a combination thereof. The object may be a phantom. Thephantom means a material having a density, an effective atomic number,and a volume that are approximately the same as those of an organism.For example, the phantom may be a spherical phantom having propertiessimilar to the physical body.

Throughout the specification, a “user” may be, but is not limited to, amedical expert including a medical doctor, a nurse, a medical laboratorytechnologist, a medial image expert, or a technician who repairs amedical apparatus.

Since a CT system is capable of providing a cross-sectional image of anobject, the CT system may distinctively express an inner structure,e.g., an organ such as a kidney or a lung, of the object, compared to ageneral X-ray imaging apparatus.

The CT system may obtain a plurality of pieces of image data with athickness not more than 2 mm several tens to several hundred times persecond and then may process the plurality of pieces of image data, sothat the CT system may provide a relatively accurate cross-sectionalimage of the object. According to the related art, only a horizontalcross-sectional image of the object can be obtained, but this issue hasbeen overcome due to various image reconstruction methods. Examples of3D image reconstruction methods are as below.

Shade surface display (SSD)—an initial 3D imaging method of displayingonly voxels having a predetermined Hounsfield Units (HU) value.

Maximum intensity projection (MIP)/minimum intensity projection(MinIP)—a 3D imaging method of displaying only voxels having thegreatest or smallest HU value from among voxels that construct an image.

Volume rendering (VR)—an imaging method capable of adjusting a color andtransmittance of voxels that constitute an image, according to areas ofinterest.

Virtual endoscopy—a method that allows endoscopy observation in a 3Dimage that is reconstructed by using the VR method or the SSD method.

Multi-planar reformation (MPR)—a method of reconstructing an image intoa different cross-sectional image. A user may reconstruct an image inany desired direction.

Editing—a method of editing adjacent voxels to allow a user to easilyobserve an area of interest in volume rendering.

Voxel of interest (VOI)—a method of displaying only a selected area involume rendering.

A CT system 100 according to an exemplary embodiment will now bedescribed with reference to FIG. 1. The CT system 100 may includevarious types of devices.

FIG. 1 schematically illustrates the CT system 100. Referring to FIG. 1,the CT system 100 may include a gantry 102, a table 105, an X-raygenerator 106, and an X-ray detector 108.

The gantry 102 may include the X-ray generator 106 and the X-raydetector 108.

An object 10 may be positioned on the table 105.

The table 105 may move in a predetermined direction (e.g., at least oneof up, down, right, and left directions) during a CT imaging procedure.Also, the table 105 may tilt or rotate by a predetermined angle in apredetermined direction.

The gantry 102 may also tilt by a predetermined angle in a predetermineddirection.

FIG. 2 is a block diagram illustrating a structure of the CT system 100.

The CT system 100 may include the gantry 102, the table 105, acontroller 118, a storage unit 124, an image processor 126, an inputunit 128, a displayer 130, and a communicator 132.

As described above, the object 10 may be positioned on the table 105. Inan exemplary embodiment, the table 105 may move in a predetermineddirection (e.g., at least one of up, down, right, and left directions),and movement of the table 105 may be controlled by the controller 118.

The gantry 102 may include a rotating frame 104, the X-ray generator106, the X-ray detector 108, a rotation driver 110, a data acquisitionsystem (DAS) 116, and a data transmitter 120.

The gantry 102 may include the rotating frame 104 having a loop shapecapable of rotating with respect to a predetermined rotation axis RA.Also, the rotating frame 104 may have a disc shape.

The rotating frame 104 may include the X-ray generator 106 and the X-raydetector 108 that are arranged to face each other to have apredetermined fields of view (FOV). The rotating frame 104 may alsoinclude an anti-scatter grid 114. The anti-scatter grid 114 may bepositioned between the X-ray generator 106 and the X-ray detector 108.

In a medical imaging system, X-ray radiation that reaches the X-raydetector 108 (or a photosensitive film) includes not only attenuatedprimary radiation that is used to generate an image but also scatteredradiation that deteriorates the quality of the generated image. Toeffectively transmit the primary radiation and to attenuate thescattered radiation, the anti-scatter grid 114 may be positioned betweenan object (or a patient) and the X-ray detector 108 (or thephotosensitive film).

For example, the anti-scatter grid 114 may be formed by alternatelystacking lead foil strips and an interspace material such as a solidpolymer material, solid polymer, or a fiber composite material. However,the anti-scatter grid 114 is not limited thereto.

The rotating frame 104 may receive a driving signal from the rotationdriver 110 and may rotate the X-ray generator 106 and the X-ray detector108 at a predetermined rotation speed. The rotating frame 104 mayreceive the driving signal and power from the rotation driver 110 whilethe rotating frame 104 contacts the rotation driver 110 via a slip ring(not shown). Also, the rotating frame 104 may receive the driving signaland power from the rotation driver 110 via wireless communication.

The X-ray generator 106 may receive a voltage and current from a powerdistribution unit (PDU) (not shown) via a slip ring (not shown) and ahigh voltage generator (not shown), and may generate and emit an X-ray.When the high voltage generator applies predetermined voltage(hereinafter, referred to as a tube voltage) to the X-ray generator 106,the X-ray generator 106 may generate X-rays having a plurality of energyspectra that correspond to the tube voltage.

The X-ray generated by the X-ray generator 106 may be emitted in apredetermined form by using a collimator 112.

The X-ray detector 108 may be positioned to face the X-ray generator106. The X-ray detector 108 may be positioned to face the X-raygenerator 106. Each of the plurality of X-ray detecting devices mayestablish a channel with the X-ray generator 106 but the exemplaryembodiments are not limited thereto.

The X-ray detector 108 may detect the X-ray that is generated by theX-ray generator 106 and transmitted through the object 10, and maygenerate an electrical signal corresponding to intensity of the detectedX-ray.

The X-ray detector 108 may include an indirect-type X-ray detector fordetecting radiation after converting the radiation into light, and adirect-type X-ray detector for detecting radiation after directlyconverting the radiation into electric charges. The indirect-type X-raydetector may use a scintillator. Also, the direct-type X-ray detectormay use a photon counting detector. The DAS 116 may be connected to theX-ray detector 108. Electrical signals generated by the X-ray detector108 may be acquired by the DAS 116. Electrical signals generated by theX-ray detector 108 may be acquired by wire or wirelessly by the DAS 116.Also, the electrical signals generated by the X-ray detector 108 may beprovided to an analog-to-digital converter (not shown) via an amplifier(not shown).

According to thickness of a slice or the number of slices, some of aplurality of pieces of data collected by the X-ray detector 108 may beprovided to the image processor 126 via the data transmitter 120, or theimage processor 126 may select some of the plurality of pieces of data.

A digital signal (or a data collected by the X-ray detector 108) may beprovided to the image processor 126 via the data transmitter 120. Thedigital signal may be provided to the image processor 126 by wire orwirelessly.

The controller 118 may control operations of the elements in the CTsystem 100. For example, the controller 118 may control operations ofthe table 105, the rotation driver 110, the collimator 112, the DAS 116,the storage unit 124, the image processor 126, the input unit 128, thedisplayer 130, the communicator 132, or the like.

The image processor 126 may receive data acquired by the DAS 116, viathe data transmitter 120, and may perform pre-processing.

The pre-processing may include, for example, a process of correcting asensitivity irregularity between channels and a process of correctingsignal loss due to a rapid decrease in signal strength or due to thepresence of an X-ray absorbing material such as metal.

Data output from the image processor 126 may be referred to as raw dataor projection data. The projection data may be stored in the storageunit 124 with imaging conditions (e.g., the tube voltage, an imagingangle, etc.) during the acquisition of data.

The projection data may be a group of data values that correspond to theintensity of the X-ray that has passed through the object 10. Forconvenience of description, a group of a plurality of pieces ofprojection data that are simultaneously obtained from a plurality ofchannels at the same imaging angle is referred to as a projection dataset.

The storage unit 124 may include at least one storage medium from amonga flash memory-type storage medium, a hard disk-type storage medium, amultimedia card micro-type storage medium, card-type memories (e.g., asecure digital (SD) card, an extreme digital (XD) memory, and the like),a random access memory (RAM), a static random access memory (SRAM), aread-only memory (ROM), an electrically erasable programmable ROM(EEPROM), a programmable ROM (PROM), a magnetic memory, a magnetic disc,and an optical disc.

The image processor 126 may reconstruct a cross-sectional image of theobject 10 by using the acquired projection data set. The cross-sectionalimage may be a 3D image. In other words, the image processor 126 mayreconstruct a 3D image of the object 10 by using a cone beamreconstruction method or the like, based on the acquired projection dataset.

The input unit 128 may receive an external input with respect to anX-ray tomography imaging condition, an image processing condition, orthe like. For example, the X-ray tomography imaging condition mayinclude tube voltages, an energy value setting with respect to aplurality of X-rays, a selection of an imaging protocol, a selection ofan image reconstruction method, a setting of an FOV area, the number ofslices, a slice thickness, a parameter setting with respect to imagepost-processing, or the like. Also, the image processing condition mayinclude a resolution of an image, an attenuation coefficient setting forthe image, setting for an image combining ratio, or the like.

The input unit 128 may include a device for receiving a predeterminedinput from an external source. For example, the input unit 128 mayinclude a microphone, a keyboard, a mouse, a joystick, a touch pad, atouch pen, a voice recognition device, a gesture recognition device, orthe like.

The displayer 130 may display an X-ray image reconstructed by the imageprocessor 126.

Exchanges of data, power, or the like between the aforementionedelements may be performed by using, for example but is not limited to,at least one of wired communication, wireless communication, and opticalcommunication.

The communicator 132 may perform communication with an external device,an external medical apparatus, etc. via a server 134 or the like.

FIGS. 3A to 3C are views illustrating a method of processing a CT imageaccording to exemplary embodiments.

There may be various scanning methods for CT imaging, for example, anaxial scanning method and a helical scanning method.

FIG. 3A illustrates CT imaging by the helix scanning method. FIG. 3Billustrates CT imaging by the axial scanning method. FIGS. 3A and 3Billustrate an example in which the CT image processing apparatusperforms the CT imaging by moving the table 105 in an axial direction ofan object (or a patient) 309. As shown in FIG. 3A, an axis parallel witha lengthwise direction (or a toe-to-head direction 303) of the object309 may be defined as a z-axis. Referring to FIG. 3B, the axial scanningmethod is a CT imaging process in which the CT image processingapparatus obtains the CT data by transmitting an X-ray to the object 309and capturing the image while the table 105 is not moved, and thentransmitting another X-ray for a predetermined period of time aftermoving the table by a predetermined distance from 307 to 308. The imageprocessor 126 reconstructs CT images 331 and 932 by using the pieces ofraw data acquired in sections 321 and 322. Electrocardiographic (ECG)gating may be used to acquire raw data that is used for reconstructionof an image.

Referring to FIG. 3A, the helical scanning method is a CT imagingprocess in which the CT image processing apparatus continuestransmitting an X-ray and capturing the image while the table 105 ismoved for a certain period of time. More specifically, the CT imageprocessing apparatus moves the table 105, on which the object 309 (or apatient including the object) is positioned, at a certain speed for acertain period of time and captures the image by continuouslytransmitting an X-ray to the object 309 while the table is moving. As aresult, the movement trajectory 305 of the X-ray light source may have aform of a helix.

FIG. 3C is a view to explain the data obtained by CT imaging accordingto the helical scanning method.

Referring to FIG. 3C, while the object 309 on the table 105 is moved,the X-ray generator 106 and the X-ray detector 108 rotates around theobject 301. In this process, the movement trajectory 305 of the X-raylight source on the X-ray generator 106 may have a form of a helix. Thedata obtained according to the movement trajectory 305 from the X-raydetector 108 may be reconstructed into a cross-sectional image based onCT images 371, 372, and 373 by using the pieces of raw data acquired insections 302, 304, and 306 of an ECG signal 360 by using the pluralityof graphics processor units (GPUs).

Referring to FIG. 3C, the movement trajectory 305 may be divided into aplurality of periods 302, 304 and 306. The data obtained during thefirst period 302, the data obtained during the second period 304 and thedata obtained during the third period 306 may be respectively processedin different GPUs. Hereinafter, an example is explained in which thethree GPUs, i.e. a first GPU, a second GPU and a third GPU are used toreconstruct one cross-sectional image. When reconstructing onecross-sectional image by using the data obtained from each section ofthe movement trajectory 305, there is interdependence among each datasource. More specifically, it is possible that by using the dataobtained from the first period 302, the second period 304 and the thirdperiod 306, the CT image processing apparatus may reconstruct onecross-sectional image, i.e. one 3D CT image. In this case, each of thedata obtained from the first period 302, the second period 304, and thethird period 306 may be processed by each of the first GPU, the secondGPU and the third GPU. By using the respectively processed data, the CTimage processing apparatus may obtain one cross-sectional image.Therefore, when the first GPU does not normally operate when processingthe data obtained in the first period 302 of the movement trajectory305, the CT image processing apparatus many not reconstruct a 3D CTimage because the data or the image which corresponds to the firstperiod 302 is not obtained.

In another exemplary embodiment, by using the data obtained from each ofthe plurality of GPUs in subsequent periods in the movement trajectory305, the CT image processing apparatus may perform anotherreconstruction operation. For example, the first GPU performs a firstoperation by using the data obtained from a subsequent period of themovement trajectory 305, the second GPU performs a second operation byusing the data obtained from the subsequent period of the movementtrajectory 305; and the third GPU performs a third operation by usingthe data obtained from the subsequent period of the movement trajectory305. Here, the first operation, the second operation and the thirdoperation may be operations of reconstructing the image required for adiagnosis of the object. In this case, when the first operation is notperformed due to a malfunction of the first GPU, the CT image processingapparatus may not obtain the data or the image which corresponds to thefirst period 302.

Therefore, when the CT image processing apparatus processes data byusing the plurality of GPUs, the CT image processing apparatus may notreconstruct a CT image when at least one GPU among the GPUs ismalfunctioning. In particular, when the image processed in themalfunctioning GPU is an image that is needed for a diagnosis, thediagnosis by the CT image processing apparatus of the object may beimpossible. Hereinafter, a method of controlling the operation of theplurality of GPUs such that a cross-sectional image is generated evenwhen a GPU is out of order.

FIG. 4 is a block diagram illustrating an apparatus for processing amedical image according to an exemplary embodiment.

The apparatus for processing a medical image according to an exemplaryembodiment includes an electronic apparatus which may generate andprocess various medical images. In detail, the apparatus for processinga medical image may include equipment that is designed to obtain theimage of an internal structure of an object. The apparatus forprocessing a medical image captures and processes the image of thestructural details of a body, the internal organs and the flow of bodyfluids and displays the image to users. The users, for example, doctors,may diagnose medical conditions and diseases by using the imagegenerated by the apparatus for processing a medical image.

The apparatus for processing a medical image may be a magnetic resonanceimaging (MRI) device, a CT imaging device, an X-ray device, or anultrasound diagnosis device, and may respectively process at least onean MRI image, a CT image, an X-ray image, or an ultrasound image.

Hereinafter, the procedure is explained by using an example in which theapparatus for processing a medical image is a CT image processingapparatus 400 for processing a tomography image.

Referring to FIG. 4, the CT image processing apparatus 400 may includean image processor 410 and a controller 420 according to an exemplaryembodiment.

The CT image processing apparatus 400 may be included in the CT system100, as shown in FIGS. 1 and 2. More specifically, the CT imageprocessing apparatus 400 may include all types of medical imagingapparatuses which reconstruct images by using data obtained by usinglight which penetrates the object.

In other words, the CT image processing apparatus 400 may include alltypes of medical imaging apparatuses which reconstruct images by usingprojection data obtained by using light which penetrates the object.More specifically, the CT image processing apparatus 400 may include aCT device, an optical coherence tomography (OCT) device, or a positronemission tomography (PET)-CT device.

Therefore, the CT image obtained by the CT image processing apparatus400, according to an exemplary embodiment, may include a CT image, anOCT image, or a PET image. In some exemplary embodiments, the CT imagemay include an image which shows the cross section of the object as anytype of image obtainable through the CT imaging; and more specifically,may be a 2D or a 3D image. Hereinafter, the image obtained from the CTimaging will be referred to as the cross-sectional image.

In some exemplary embodiments, when the CT image processing apparatus400 is included in the CT system 100 as shown in FIG. 1, the imageprocessor 410 shown in FIG. 2 may be included in the image processor 126shown in FIG. 1, and the controller 420 may be included in thecontroller 118 shown in FIG. 1.

The image processor 410, according to an exemplary embodiment, mayinclude processors which reconstruct the cross-sectional image based onthe CT image obtained from the CT imaging of at least one object. Inthis specification, a processor may refer to a device which may performthe calculation needed to reconstruct the cross-sectional image.Examples of processors may include a GPU, a central processor (CPU), amicro processor unit (MPU), a micro controller unit (MCU), and a digitalsignal processor (DSP). Hereinafter, according to an exemplaryembodiment, a detailed explanation is given with an example in which theprocessor is a GPU. The image processor 410 may include a plurality ofGPUs GPU 0, GPU 1, GPU 2 . . . GPU N. In this context, CT data is dataused for reconstructing the cross-sectional image, and may be projectiondata or a sinogram which is raw data obtained from the CT imaging.

In this context, the object may include a human being or an animal or apart of the human being or the animal which is the target of the CTimaging. In some exemplary embodiments, at least one object may includea plurality of objects. Hereinafter, a detailed explanation is given byusing an example in which a first object refers to at least a part of apatient “X” and a second object refers to at least a part of a patient“Y” who is different from the patient “X.”

The controller 420 monitors whether the plurality of GPUs normallyfunction and, based on a result of the monitoring, may assign at leastone of a primary operation which is a reconstruction stage of across-sectional image with a higher priority and a secondary operationwhich is a reconstruction stage of a cross-sectional image with a lowerpriority to at least one of the plurality of GPUs.

The controller 420 may control the primary operation which has a higherpriority to be processed prior to the second operation. To this end, thecontroller 420 may assign the primary operation or the secondaryoperation to each of GPUs such that the number of GPUs which perform theprimary operation exceeds the number of GPUs which perform the secondaryoperation. For example, controller 420 may assign the primary operationto four of a total of six GPUs and assign the secondary operation to theremaining two GPUs in response to detecting a malfunction of the GPUs.

The controller 420 may assign the primary operation and the secondaryoperation to the GPUs that are not found to be out of order among theplurality of GPUs when the controller 420 determines, based on theresult of monitoring the GPUs, that at least one or more GPUs aremalfunctioning. For example, the controller 420 may assign the primaryoperation to four GPUs that are not found to be out of order and thesecondary operation to one GPU that is not found to be out of order whenthe controller 420 determines that one of the total of six GPUs is outof order.

As described above, the controller 420 may individually assign theoperation of image reconstruction to each GPU based on the priorities.Accordingly, even if at least one or more GPUs are malfunctioning amongthe plurality of GPUs, the primary operation and the secondary operationmay be still performed. An example of a method of assigning the primaryand secondary operations will be explained in detail by referring toFIGS. 7 through 9.

The primary operation according to an exemplary embodiment refers to anoperation of reconstructing the cross-sectional image which has a toppriority (i.e. a first priority) among a plurality of operations ofreconstructing the cross-sectional image. For example, the primaryoperation may be the operation of reconstructing the cross-sectionalimage of a first object based on the CT data obtained by CT imaging ofthe first object while the CT image processing apparatus 400 performsthe CT imaging on the first object.

The reconstructing the cross-sectional image generated by the primaryoperation, is performed at the same time as the CT imaging so that usersmay verify in real time the reconstructed cross-sectional image. Inother words, the reconstructed cross-sectional image of the first objectgenerated by the primary operation may be displayed while the CT imagingis being performed. The primary operation may be referred to as a livereconstruction. Hereinafter, the reconstructed cross-sectional imagegenerated by the primary operation is referred to as the firstcross-section image.

The primary operation may be performed by using such reconstructiontypes as back-projection filtering and filtered back-projection, butthese are just examples and the primary operation is not limitedthereto.

The secondary operation according to an exemplary embodiment is anoperation of reconstructing the cross-sectional image which has a secondpriority, and has a lower priority than the primary operation which hasthe top priority. In detail, the secondary operation is an operation ofreconstructing the cross-sectional image which the user intends tofurther verify after verifying the first cross-sectional image. Sincethe secondary operation has a lower priority than the primary operation,the secondary operation may be performed slower than the primaryoperation. In some exemplary embodiments, the secondary operation isperformed independently because the secondary operation is differentfrom the primary operation. When the secondary operation is performed,the CT image processing apparatus may reconstruct the cross-sectionalimage which is not displayed during the process of CT imaging of thefirst object but displayed after the imaging is completed. Hereinafter,the reconstructed cross-sectional image generated by the secondaryoperation is referred to as a second cross-sectional image.

The secondary operation may be initiated concurrently with the livereconstruction of the first object. In some exemplary embodiments, thesecondary operation may be initiated during and even after the livereconstruction of the first object. Initiating and/or controlling thesecondary operation may be performed in response to by an input signalof the user.

The secondary operation according to an exemplary embodiment may includea scan reconstruction.

The scan reconstruction is an operation of reconstruction performedindependently from the primary operation and refers to reconstructingthe second cross-sectional image by using the CT data based on thereconstruction method which is different from the reconstruction methodfor the primary operation.

The user may boost the accuracy of diagnosis by verifying the imagereconstructed by the scan reconstruction which is performed differentlyfrom the reconstruction by the live reconstruction. More specifically,live reconstruction and scan reconstruction are different in terms ofmethods of reconstructing the image, processing the image, anddisplaying the image which shows the identical object differently. Thetypes of reconstruction used in the scan reconstruction may be selectedby a user input. Therefore, when the user inputs corresponding tocommands for a plurality of types of reconstruction executable by thescan reconstruction, the scan reconstruction may be performed multipletimes.

In some exemplary embodiments, the scan reconstruction may be providedto post-process the removal of the artifacts of the cross-sectionalimage.

The scan reconstruction may be performed concurrently with the primaryoperation, because the scan reconstruction uses data identical to thedata used for the CT imaging.

According to an exemplary embodiment, the secondary operation mayinclude a post reconstruction.

The post reconstruction may be an operation performed to complement thelive reconstruction when the user verifies the cross-sectional imagereconstructed by live reconstruction, after the live reconstruction ofthe first object is completed. In some exemplary embodiments, the postreconstruction may be an operation of reconstruction performed tocomplement the scan reconstruction after the user verifies thecross-sectional image reconstructed by scan reconstruction.

When used with post reconstruction, the CT image processing apparatusmay generate the second cross-sectional image of the first object, basedon at least one of the CT data and the first cross-sectional image.

For example, when the user wants to remove noise from the reconstructedimage obtained by the live reconstruction and/or scan reconstruction, orwhen the user wants to remove metal artifacts which appear on thereconstructed image, the user may perform the post reconstruction.

In some exemplary embodiments, the user may perform the postreconstruction to remove various artifacts which appear on thereconstructed cross-sectional image.

For example, when the user wants to remove the artifacts on the livereconstruction image, or when the user wants to remove the artifacts onthe reconstructed cross-sectional image obtained by the scanreconstruction, the user may perform the post reconstruction to removethe artifacts. In addition, the user may perform the post reconstructionwhen selecting another reconstruction method that is different from thereconstruction methods used for the live reconstruction and scanreconstruction.

The aforementioned reconstruction method used for the scanreconstruction and/or post reconstruction may be a non-iterativereconstruction such as filtered back projection or an iterativereconstruction. In addition, the reconstruction of the image may beperformed in many different ways, and is not limited to the specificmethods described above.

FIG. 5 is a block diagram of a CT image processing apparatus 500according to an exemplary embodiment.

Referring to FIG. 5, the CT image processing apparatus 500 according toan exemplary embodiment includes the image processor 510, the controller520, the displayer 540 and the input unit 550.

The image processor 510 and the controller 520 shown in FIG. 5 may besimilar to or substantially the same as the image processor 410 and thecontroller 420 shown in FIG. 4, respectively, and thus detaileddescriptions thereof will be omitted. Similarly, the displayer 540 andthe input unit 550 shown in FIG. 5 may be similar to or substantiallythe same as the input unit 128 and the displayer 130 of the CT system100 shown in FIG. 1, respectively, and thus detailed descriptionsthereof will be omitted.

The displayer 540 displays a predetermined screen. More specifically,the displayer 540 may display the reconstructed cross-sectional image.The reconstructed cross-sectional image may be the first cross-sectionalimage reconstructed by the primary operation or the secondcross-sectional image reconstructed by the secondary operation.

The displayer 540 may display the first cross-sectional imagereconstructed by the primary operation while the CT imaging of the firstobject is underway.

In some exemplary embodiments, the displayer 540 may display a userinterface screen. For example, the displayer 540 may display a userinterface screen for selecting the type of reconstructing and processingapplicable to the scan reconstruction, a user interface screen forselecting the type of reconstructing and processing applicable to thelive reconstruction, and a user interface screen for selecting the typeof reconstructing and processing applicable to the post reconstruction.The displayer 540 may display the user interface screen for setting theassignment of the plurality of GPUs.

The displayer 540 may display a user interface screen which indicates acurrent status of the CT image processing apparatus 500. In detail, thedisplayer 540 may display the user interface screen which indicates thecurrent operation status of each of the plurality of the GPUs of the CTimage processing apparatus 500.

The displayer 540 may display an error message which informs the user ofthe malfunctioning GPUs when one or more of the plurality of the GPUsare detected to be out of order. When one or more of the plurality ofthe GPUs of the CT image processing apparatus 500 are detected to be outof order, the controller 520 may control the CT image processingapparatus to inform an external device or an external medical apparatusof malfunction occurring in the GPUs. In some exemplary embodiments, thecontroller 520 may transmit an alarm signal, via a communicator (132 inFIG. 2), to a user or a manufacturer of the CT image processingapparatus to indicate that one or more of the GPUs are detected to beout of order. For example, the alarm signal includes an auditory signal.

The input unit 550 may receive from the user predetermined data,requests, or commands. For example, the input unit 550 may receive thepredetermined data or requests through the user interface screen.

Specifically, the input unit 550 may receive an input for the secondaryoperation and the image processor 510 may determine whether to performthe secondary operation and the method of reconstructing the image ofthe secondary operation based on the input.

The user may determine whether to perform the secondary operation andthe method of reconstructing the image of the secondary operation whenthe user confirms the first cross-sectional image displayed on thedisplayer 540 after the primary operation is performed.

FIG. 6 is a flowchart of a method of processing a CT image according toan exemplary embodiment. The method of processing the CT image accordingto an exemplary embodiment may be used to reconstruct a cross-sectionalimage of an object based on CT data obtained by CT imaging at least oneobject.

Referring to FIG. 6, in operation S610, the CT image processingapparatus may detect whether at least one of the plurality of graphicprocessors (GPU) malfunction (S610). The plurality of GPUs may beincluded in the CT image processing apparatus to execute reconstructingof the cross-sectional image of the object. Operation S610 may beperformed by the controller 410 of the CT image processing apparatus 400or by the controller 510 of the CT image processing apparatus 500,according to an exemplary embodiment.

In operation S620, the CT image processing apparatus may assign imagereconstruction determined by priorities to each GPU based on a result ofdetecting a malfunction (S620). More specifically, in operation S620 theCT image processing apparatus may assign to at least one of theplurality of GPUs at least one of either a primary operation which isthe reconstruction stage of a cross-sectional image with a higherpriority or a secondary operation which is the reconstruction stage of across-sectional image with a lower priority. Operation S620 may beperformed by the controller 410 of the CT image processing apparatus 400or by the controller 510 of the CT image processing apparatus 500,according to an exemplary embodiment.

FIG. 7 is a view illustrating an example of assigning priorities in amethod of processing a CT image according to an exemplary embodiment.

FIG. 7 illustrates assigning mage reconstruction operations to each of atotal of six GPUs included in the CT image processing apparatus. FIG. 7shows an example in which all of the six GPUs GPU 0, GPU 1, GPU 2, GPU3, GPU 4, and GPU 5 normally operate.

First reconstruction 710 may refer to a reconstruction operation whichhas a first priority. For example, the first reconstruction 710 may bethe aforementioned live reconstruction.

Second reconstruction 720 and third reconstruction 730 may refer tosecond-priority reconstruction operations which have a lower prioritythan the first priority. The second reconstruction 720 operation and thethird reconstruction 730 operation may be included in the secondaryoperation.

For example, the second reconstruction 720 may be the aforementionedscan reconstruction. For example, the third reconstruction 730 may bethe aforementioned post reconstruction.

The first reconstruction 710, which is an operation that has the firstpriority, may be assigned to the four GPUs 750 including GPU 0, GPU 1,GPU 2, and GPU 3 among the GPUs GPU 0 to GPU 5. The secondreconstruction 720, which is an operation that has the second priority,may be assigned to a GPU 760 including GPU 4; 760 among the GPUs GPU 0to GPU 5. The third reconstruction 730, which is an operation that hasthe second priority, may be assigned to a GPU 770 GPU 5 among the GPUsGPU 0 to GPU 5.

Accordingly, the number of GPUs included in the GPUs 750 which areassigned the first reconstruction 710 which has the first priority isgreater than that of GPU included in the GPU 760 which is assigned thesecond reconstruction 720 which has the second priority and that of aGPU included in the GPU 770 which is assigned the third reconstruction730 which has the second priority. Therefore, the first reconstruction710 which has the first priority may be processed faster than the secondreconstruction 720 and the third reconstruction 730.

Therefore, according to an exemplary embodiment, the live reconstructionmay be processed faster than the scan reconstruction and the postreconstruction so that the user may verify the cross-sectional image inreal time.

FIG. 8A is a view illustrating an example of assigning priorities in amethod of CT image processing according to an exemplary embodiment.

FIG. 8A illustrates an example in which a GPU 2 803 is detected to beout of order while a GPU 0 801, GPU 1 802, GPU 3 805, GPU 4 807 and GPU5 808 normally operate among a total of six GPUs GPU 0, GPU 1, GPU 2,GPU 3, GPU 4, and GPU 5.

When the GPU 2 803 in FIG. 8A is detected to be out of order, the CTimage processing apparatus may assign the operation of reconstructingthe image to each of the remaining GPUs GPU 0, GPU 1, and GPU 3 to GPU 5except for the GPU 2 803 which is detected to be out of order.

For example, a first reconstruction 810 may be assigned to GPU 0 801,GPU 1 802, GPU 3 805, and GPU 4 807, while a second reconstruction 820and a third reconstruction 830 may be assigned to the GPU 5 805.

According to an exemplary embodiment, when the second reconstruction 820and the third reconstruction 830 which have lower priorities areassigned to the GPU 5 805, the GPU 5 805 may perform the thirdreconstruction 830 after the second reconstruction 820 is completed. Forexample, the CT image processing apparatus may be configured to controlsuch that the post reconstruction is performed by the GPU 5 805 afterthe scan reconstruction is completed.

Accordingly, the CT image processing apparatus may ensure the first,second and third reconstruction operations normally function even whenthe GPU 2 803 is detected as being out of order, by assigning both thesecond and third reconstruction operations with lower priorities to theGPU 5 805.

At the same time, the CT image processing apparatus may maintain thespeed of processing the first reconstruction operation regardless ofwhether a malfunction occurs in any of the GPUs GPU 1 to GPU 5, byassigning the first reconstruction operation to four GPUs GPU 0 801, GPU1 802, GPU 3 805, and GPU 4 807.

FIG. 8B is a view illustrating an example of assigning priorities in amethod of processing a CT image according to an exemplary embodiment.

FIG. 8B illustrates an example in which GPU 0 801, GPU 4 807, and GPU 5808 among six GPUs GPU 0, GPU 1, GPU 2, GPU 3, GPU 4, and GPU 5 normallyoperate while the remaining GPUs GPU 1 02, GPU 2 803, and GPU 3 805 aredetected to be out of order.

When GPU 1 802, GPU 2 803, and GPU 3 805 shown in FIG. 8B are detectedto be out of order, the CT image processing apparatus may assign anoperation of reconstructing the image to each of the remaining threeGPUs GPU 1 to GPU 3 except for the GPU 1 802, GPU 2 803, and GPU 3 805which are detected to be out of order.

For example, the first reconstruction 810 may be assigned to GPU 0 801and GPU 4 807, while the second reconstruction 820 and the thirdreconstruction 830 to the GPU 5 805.

An exemplary embodiment shown in FIG. 8B illustrates an example in whichthree GPUs among a total of six GPUs do not normally operate. Therefore,the CT image processing apparatus may assign two GPUs instead of fourGPUs, to ensure the first, second and third reconstruction operationsare performed properly.

According to an exemplary embodiment shown in FIGS. 8A and 8B, the firstreconstruction operation is processed faster than the second and thirdreconstruction operations.

In other words, in the method of processing the CT image according to anexemplary embodiment, the CT image processing apparatus may assign theprimary operation to as many GPUs as possible, based on the total numberof GPUs and the number of GPUs detected to be out of order. In someexemplary embodiments, the CT image processing apparatus may assign theprimary operation to more GPUs than the secondary operation.

Accordingly, the speed of processing the primary operation may be fasterthan that of the secondary operation with a lower priority.

FIG. 9 is view illustrating an example of assigning priorities in amethod of processing a CT image according to another exemplaryembodiment.

FIG. 9 illustrates an example in which the CT image processing apparatusassigns an operation of reconstructing the image to each of eight GPUs.FIG. 9 illustrates an example in which all of eight GPUs GPU 0, GPU 1,GPU 2, GPU 3, GPU 4, GPU 5, GPU 6, and GPU 7 normally operate.

A first reconstruction 910 which has the first priority may be assignedto for GPUs 950 including GPU 0, GPU 1, GPU 2, and GPU 3 among the eightGPUs. A second reconstruction 720 which has the second priority may beassigned to two GPUs 960 including GPU 4 and GPU 5 among the eight GPUsGPU 0 to GPU 7. A third reconstruction 930 which has the second prioritymay be assigned to two GPUs 970 including GPU 6 and GPU 7 among theeight GPUs.

Similar to the exemplary embodiments described in FIGS. 7, 8A, and 8B,in FIG. 9, the number of GPUs 950 which are assigned the firstreconstruction 910 having the first priority is greater than that ofGPUs 960 which are assigned the second reconstruction 920 having thesecond priority and greater than that of GPUs 970 which are assigned thethird reconstruction 930 which has the second priority. Therefore, thefirst reconstruction 910 which has the first priority may be processedfaster than the second reconstruction 920 and the third reconstruction930. In FIG. 9, two more GPUs are additionally included in the CT imageprocessing apparatus than in the exemplary embodiments described inFIGS. 7, 8A and 8B, and the first reconstruction 910 may be assigned tothe additionally included two GPUs.

FIG. 10 is a view illustrating an example of assigning priorities in amethod of processing a CT image according to another exemplaryembodiment.

FIG. 10 illustrates an example in which GPU 0 1001, GPU 4 1009, GPU 51011, GPU 6 1013, and GPU 7 1015 among all of eight GPUs GPU 0, GPU 1,GPU 2, GPU 3, GPU 4, GPU 5, GPU 6, and GPU 7 normally operate while GPU1 1003, GPU 2 1005, and GPU 3 1007 are detected to be out of order.

When the GPU 1 1003, GPU 2 1005 and GPU 3 1007 are detected to be out oforder, the CT image processing apparatus may assign the operation ofreconstructing the image to each of the remaining five GPUs except forthe GPU 1 1003, GPU 2 1005, and GPU 3 1007 which are detected to be outof order.

For example, the CT image processing apparatus may assign a firstreconstruction 1010 to GPU 0 1001, GPU 4 1009, GPU 5 1011 and GPU 6 1013while assigning a second reconstruction 1020 and a third reconstruction1030 to the GPU 7 1015.

The exemplary embodiment described in FIG. 10 illustrates an example inwhich three GPUs GPU 1 to GPU 3 do not normally operate among a total ofeight GPUs GPU 0 to GPU 7. Therefore, the CT image processing apparatusmay ensure that the first, second and third reconstruction operationsare normally performed even when the GPU, which performs a primaryoperation, is out of order, by concurrently assigning both the secondand third reconstruction operations having lower priorities to anotherGPU.

In FIG. 10, there are two more GPUs than in the exemplary embodimentsdescribed in FIGS. 7, 8A and 8B, and the CT image processing apparatusmay maintain the speed of processing the first reconstruction operationthe same regardless of whether a malfunction occurs in any of the GPUsGPU 0 to GPU 7 by assigning the first reconstruction operation to fourGPUs GPU 0 and GPU 4 to GPU 6.

In the method of processing the CT image according to an exemplaryembodiment, the CT image processing apparatus may assign the primaryoperation to as many GPUs as possible, based on the total number of GPUsand the number of GPUs detected to be out of order. In some exemplaryembodiments, the CT image processing apparatus may assign the primaryoperation to more GPUs than the secondary operation.

Therefore, the first reconstruction operation which has the firstpriority may be processed faster than the second reconstructionoperation.

FIGS. 11A and 11B are sequence diagrams of a method of processing a CTimage according to an exemplary embodiment. FIGS. 12A and 12B aresequence diagrams of a method of processing a CT image by a CT imageprocessing apparatus according to another exemplary embodiment.

FIGS. 11A, 11B, 12A, and 12B illustrate a procedure in which a CT dataacquirer 1101 acquires the CT data of first and second objects, andfirst, second and third reconstruction operations are performed by aplurality of GPUs in an image processor 410 or 510.

The CT data acquirer 1101 may acquire CT data by capturing an image ofat least one object through CT imaging. The CT data acquirer 1101 shownin FIGS. 11A to 12B may be included in the gantry 102 shown in FIG. 2.

A GPU 1103 is a GPU which performs a first operation of reconstructionwhile a GPU 1105 is a GPU which performs a second operation ofreconstruction and a GPU 1107 is a GPU which performs a third operationof reconstruction. Each of the GPU 1103, GPU 1105, and GPU 1107 may bemultiple in number.

The first, second, and third reconstruction operations may correspond tothe first, second, and third reconstruction operations which aredescribed in relation to FIGS. 7 through 10. FIGS. 11A, 11B, 12A, and12B illustrates an example in which the first reconstruction operationis a live reconstruction operation while the second reconstructionoperation is a scan reconstruction operation and the thirdreconstruction operation is a post reconstruction operation.

FIGS. 11A and 11B illustrate an example in which the first, second, andthird reconstruction operations are performed when the plurality of GPUsare not detected to be out of order. The GPU 1105 which performs thesecond operation of reconstruction may be different from the GPU 1107which performs the third operation of reconstruction.

The first, second, and third reconstruction operations may be assignedto the plurality of GPUs (S1101). The first reconstruction operation1102, the second reconstruction operation 1103, and the thirdreconstruction operation 1104 may be assigned according to the methodwhich is described in relation to FIGS. 7 through 10.

Referring to FIGS. 11A and 11B, the CT data acquirer 1101 may performthe CT imaging of the first object (S1102). The CT data acquirer maytransmit the CT data obtained from the first object to the GPU 1103 andthe GPU 1105 (S1103).

In the GPU 1103 which is assigned the first reconstruction operation,the CT image processing apparatus may perform the live reconstruction onthe first object, based on the CT data (S1104). In the GPU 1105 which isassigned the second reconstruction operation, the CT image processingapparatus may perform the live reconstruction of the first object, basedon the CT data (S1107).

The CT data acquirer 1101 may transmit the CT data obtained with respectto the first object to the GPU 1107 (S1108). After the livereconstruction of the first object is completed (S1105), the CT dataacquirer 1101 may perform the post reconstruction of the first object atthe GPU 1107 (S1111). The CT data acquirer 1101 may complete the scanreconstruction of the first object at the GPU 1105 (S1109).

On the other hand, the CT data acquirer 1101 may perform the CT imagingon the second object that is different from the first object (S1115). Insome exemplary embodiments, the CT data acquirer 1101 may transmit theCT data of the second object to the GPU 1103 and the GPU 1105 (S1116).

In a similar manner as described with respect to the first object, thelive reconstruction may be performed also for the second object by theGPU 1103 (S1117). In some exemplary embodiments, the scan reconstructionmay be performed concurrently also for the second object by the GPU 1105(S1121).

While the live reconstruction and the scan reconstruction for the secondobject are being performed, the post reconstruction for the first objectmay be completed by the GPU 1107 (S1113).

The CT data acquirer 1101 may transmit the CT data obtained with respectto the second object to the GPU 1107 (S1108). After the livereconstruction of the second object is completed (S1119), the CT dataacquirer 1101 may perform the post reconstruction of the second objectin the GPU 1107 (S1125).

After the scan reconstruction is completed on the second object by theGPU 1105 (S1123), the post reconstruction may be completed on the secondobject by the GPU 1107 (S1127).

As described above with reference to FIGS. 7 through 10, it may takemore time to perform the secondary operation (e.g., scan reconstructionand/or post reconstruction) which has lower priorities than to performthe primary operation (e.g., live reconstruction) which has the toppriority. In other words, it may take more time to perform the scanreconstruction on the first object, to perform the post reconstructionon the first object, to perform the scan reconstruction on the secondobject, and to perform the post reconstruction on the second object thanto perform the live reconstruction on the first object and/or the secondobject.

FIGS. 12A and 12B illustrate an example in which, when some of theplurality of GPUs are detected to be out of order, the first, second,and third reconstruction operations are performed. In this case, the GPU1105 which performs the second operation of reconstruction may beidentical with the GPU 1107 which performs the third operation ofreconstruction in FIGS. 12A and 12B.

The exemplary embodiments of FIGS. 12A and 12B may be similar to or thesame as the exemplary embodiments as shown in FIGS. 11A and 11B exceptfor the fact that GPU 1105 and GPU 1107 may be identical. Therefore, thedescription below will focus on the differences therebetween.

First of all, the first, second, and third reconstruction operations maybe assigned to the plurality of GPUs (S1101). The first reconstructionoperation 1102, the second reconstruction operation 1103, and the thirdreconstruction operation 1104 may be assigned according to the methodwhich is described in relation to FIGS. 7 through 10.

Referring to FIGS. 12A and 12B, the CT data acquirer 1101 may performthe CT imaging of the first object (S1102). The CT data acquirer 1101may transmit the CT data obtained with respect to the first object tothe GPU 1103 and the GPU 1105 (S1103).

By using the GPU 1103 which is assigned the first reconstructionoperation, the CT image processing apparatus may perform the livereconstruction of the first object, based on the CT data (S1104). At thesame time, by using the GPU 1105 which is assigned the secondreconstruction operation, the CT image processing apparatus may performthe scan reconstruction of the first object, based on the CT data(S1107).

After the scan reconstruction on the first object is completed in theGPU 1105 (S1109), the post reconstruction on the first object may beperformed (S1111). Once the post reconstruction on the first object iscompleted (S1113), the scan reconstruction on the second object, inturn, may be performed (S1121).

In other words, as the second operation of reconstruction and the thirdoperation of reconstruction are performed by the identical GPU 1105,there is a time interval from a time point when the moment the livereconstruction on the first object is completed in operation S1104 to atime point when the post reconstruction is performed on the first objectin operation S1111.

In some exemplary embodiments, the task of performing the scanreconstruction may not be initiated concurrently with the livereconstruction on the second object. Therefore, there may be a timeinterval from a time point when the scan reconstruction on the firstobject is completed in operation S1109 to a time point when the scanreconstruction on the second object is performed in operation S1121.

According to an exemplary embodiment shown in FIGS. 12A and 12B, as thelive reconstruction which has the top priority may be processed fasterthan the second and third reconstruction operations, the livereconstruction on the second object may be performed (S1117) while thepost reconstruction on the first object is performed (S1111).

In other words, it may be possible that while the cross-sectional imageof a patient X is being post-processed, the user may verify a result ofCT imaging on a patient Y by live reconstruction in real time.

FIGS. 13A, 13B, and 13C are views illustrating a user interface screenwhich indicates an operation status of each of a plurality of GPUs of anapparatus for processing a medical image.

As described above, the displayer 540 may display the user interfacescreen which indicates a current status of the CT image processingapparatus 500. In detail, the displayer 540 may display the userinterface screen which indicates the current operation status of each ofthe plurality of the GPUs of the CT image processing apparatus 500.

FIG. 13A illustrates a user interface screen 1200 a which indicates theoperation status of the CT image processing apparatus 500 which includessix GPUs.

The user interface screen 1200 a may include a user interface 1210 whichindicates a use status of the GPUs configured to reconstructcross-sectional images.

Referring to FIG. 13A, all of six GPUs GPU 0, GPU 1, GPU 2, GPU 3, GPU4, and GPU 5 of the CT image processing apparatus 500 may normallyoperate.

The CT image processing apparatus 500 may assign the firstreconstruction operation which has a first priority (or a top priority)to four GPUs among the six GPUs GPU 0 to GPU 5. For example, the CTimage processing apparatus 500 may assign a first reconstructionoperation to GPU 0, GPU 1, GPU 2, and GPU 3. The first reconstructionoperation may include a live reconstruction.

In some exemplary embodiments, the CT image processing apparatus 500 mayassign a second reconstruction operation which has a second priority (ora second highest priority) to one GPU among the six GPUs GPU 0 to GPU 5.For example, the CT image processing apparatus 500 may assign the secondreconstruction operation to the GPU 4. The second reconstructionoperation may include a scan reconstruction.

In some exemplary embodiments, the CT image processing apparatus 500 mayassign a third reconstruction operation which has a second priority (ora lowest priority) to one GPU among the six GPUs GPU 0 to GPU 5. Forexample, the CT image processing apparatus 500 may assign the thirdreconstruction operation to the GPU 5. The third reconstructionoperation may include a post reconstruction.

The displayer 540 may display a use rate for each of the GPUs of the CTimage processing apparatus 500. In detail, the displayer 540 may displayan indicator bar 1211 which indicates the use rate of the GPU, alongwith the use rate 1213 of the GPU.

Referring to FIG. 13A, for example, while the CT image processingapparatus 500 is performing the first reconstruction operation, the userate of the GPU 0, GPU 1, GPU 2, and GPU 3 may be 63%, for each of theGPUs. While the CT image processing apparatus 500 is performing thesecond reconstruction operation, the use rate of the GPU 4 may be 40%.While the CT image processing apparatus 500 is not performing the thirdreconstruction operation, the use rate of the GPU 5 may be 0%.

FIG. 12B illustrates a user interface screen 1200 b which shows theoperation status of the CT image processing apparatus 500 which includessix GPUs.

The user interface screen 1200 b may include a user interface 1220 whichindicates the use status of GPUs GPU 0, GPU 1, GPU 2, GPU 3, GPU 4, andGPU 5 to reconstruct the cross-sectional image.

Referring to FIG. 13B, the GPU 0, the GPU 1, the GPU 3, the GPU 4, andthe GPU 5 among the GPUs GPU 0 to GPU 5 of the CT image processingapparatus 500 may normally operate while the GPU 2 may not normallyoperate.

The displayer 540 may display an error message which informs the user ofthe malfunctioning GPU when one or more of the plurality of the GPUs GPU0 to GPU 5 are detected to be out of order.

For example, as shown in FIG. 13B, the displayer 540 may display anerror message 1221 which informs the user of the malfunction of the GPU2 when the GPU 2 is detected to be out of order.

The CT image processing apparatus 500 may assign the imagereconstruction operation to each of the remaining five GPUs except forthe GPU 2 which is detected to be out of order.

For example, the CT image processing apparatus 500 may assign the firstreconstruction operation to the GPU 0, the GPU 1, the GPU 3, and the GPU4. In an exemplary embodiment, the first reconstruction operation mayinclude the live reconstruction. The CT image processing apparatus 500may assign the second and third reconstruction operations concurrentlyto the GPU 5. For example, the second reconstruction operation mayinclude the scan reconstruction, and the third reconstruction operationmay include the post reconstruction.

FIG. 13C illustrates a user interface screen 1200 c which shows theoperation status of the CT image processing apparatus 500 which includessix GPUs.

The user interface screen 1200 c may include the user interface 1230which indicates the use status of the GPUs which reconstructcross-sectional images.

Referring to FIG. 13C, the GPU 0, the GPU 4, and the GPU 5 among theGPUs GPU 0 to GPU 5 of the CT image processing apparatus 500 maynormally operate while the GPU 1, the GPU 2, and the GPU 3 may notnormally operate.

The CT image processing apparatus 500 may assign the imagereconstruction operation to each of the remaining 3 GPUs except for theGPU 1, GPU 2, and GPU 3 which are detected to be out of order, when theGPU 1, GPU 2, and GPU 3 are detected to be out of order.

For example, the CT image processing apparatus 500 may assign the firstreconstruction operation to the GPU 0 and GPU 4. In an exemplaryembodiment, the first reconstruction operation may include the livereconstruction. The CT image processing apparatus 500 may concurrentlyassign the second and third reconstruction operations to the GPU 5. Forexample, the second reconstruction operation may include the scanreconstruction, and the third reconstruction operation may include thepost reconstruction.

The CT image processing apparatus 500 may assign the firstreconstruction operation to two GPUs instead of four GPUs compared tothe exemplary embodiments of FIGS. 13A and 13B, when three GPUs amongall of the six GPUs GPU 0 to GPU 5 are detected to be out of order.

When the 3 GPUs are out of order as shown in FIG. 13C, a use rate 1233of the GPU 0 shown in FIG. 13C may be higher than a use rate 1213 of theGPU 0 shown in FIG. 13A.

The user may monitor to determine which one of the GPUs included in theCT image processing apparatus 500 is out of order, through the userinterface screens 1200 a, 1200 b, and 1200 c as shown in FIGS. 13A to13C. In some embodiments, the user may monitor a use amount of thepluralities of the GPUs during the reconstruction operation of the CTimage processing apparatus 500.

The exemplary embodiments can be written as computer programs and can beimplemented in general-use digital computers that execute the programsusing a non-transitory computer readable recording medium.

Examples of the non-transitory computer readable recording mediuminclude magnetic storage media (e.g., ROMs, floppy disks, hard disks,etc.), optical recording media (e.g., compact disk (CD)-ROMs, or digitalversatile disks (DVDs)), etc.

At least one of the components, elements or units represented by a blockas illustrated in FIGS. 2, 4, and 5 may be embodied as various numbersof hardware, software and/or firmware structures that execute respectivefunctions described above, according to an exemplary embodiment. Forexample, at least one of these components, elements or units may use adirect circuit structure, such as a memory, processing, logic, a look-uptable, etc. that may execute the respective functions through controlsof one or more microprocessors or other control apparatuses. Also, atleast one of these components, elements or units may be specificallyembodied by a module, a program, or a part of code, which contains oneor more executable instructions for performing specified logicfunctions. Also, at least one of these components, elements or units mayfurther include a processor such as a central processing unit (CPU) thatperforms the respective functions, a microprocessor, or the like.Further, although a bus is not illustrated in the above block diagrams,communication between the components, elements or units may be performedthrough the bus. Functional aspects of the above exemplary embodimentsmay be implemented in algorithms that execute on one or more processors.Furthermore, the components, elements or units represented by a block orprocessing steps may employ any number of related art techniques forelectronics configuration, signal processing and/or control, dataprocessing and the like.

Although a few embodiments have been shown and described, it would beappreciated by those skilled in the art that changes may be made in theexemplary embodiments without departing from the principles and spiritof the disclosure, the scope of which is defined in the claims and theirequivalents.

What is claimed is:
 1. An apparatus for processing a medical image, theapparatus comprising: a display; an image processor comprising aplurality of processors, each of the plurality of processors beingconfigured to be assigned to one of a first operation having a firstpriority and a second operation having a second priority lower than thefirst priority, to reconstruct a cross-sectional image of an object; anda controller, operatively coupled to the display, configured to detectwhether a malfunction occurs among the plurality of processors, andconfigured to, when the malfunction occurs in a processor assigned tothe first operation, perform at least one of reassigning the firstoperation, to the plurality of processors such that a number of theplurality of processors assigned to the first operation is maintainedand changing use rate of the plurality of processors assigned to thefirst operation.
 2. The apparatus of claim 1, wherein the controller isconfigured to increase the use rate of the plurality of processorsexcept for the processor in which the malfunction is detected.
 3. Theapparatus of claim 1, wherein the controller is configured to update theuse rate for each of the plurality of processors assigned to the firstoperation and display the use rate for each of the plurality ofprocessors.
 4. The apparatus of claim 1, wherein the controller isconfigured to display zero percent of use rate for the processor inwhich the malfunction is detected.
 5. The apparatus of claim 1, whereinthe controller is configured to reassign the second operation, to theplurality of processors such that a number of the plurality ofprocessors assigned to the second operation is reduced.
 6. The apparatusof claim 1, wherein the controller is configured to update at least oneof the plurality of processors assigned to the first operation anddisplay the plurality of processors assigned to the first operation. 7.The apparatus of claim 1, wherein the controller is configured todisplay which operation is assigned to the plurality of processors. 8.The apparatus of claim 1, wherein the controller is configured todisplay an user interface that indicate the processor in which themalfunction is detected.
 9. The apparatus of claim 1, wherein thecontroller is configured to display a first cross-sectional imagegenerated by using the first operation while CT imaging is beingperformed on the object.
 10. The apparatus of claim 9, wherein thecontroller is configured to display a second cross-sectional imagegenerated by the second operation, the second operation being performedon the object after CT imaging of the object is completed.
 11. Theapparatus of claim 10, wherein the second operation comprises a scanreconstruction, and the scan reconstruction is performed byreconstructing the second cross-sectional image by using CT data in amanner different from reconstructing the first cross-sectional image byusing the first operation.
 12. The apparatus of claim 11, wherein thesecond operation further comprises post reconstruction by which thesecond cross-sectional image of the object is generated based on atleast one of the CT data and the first cross-sectional image.
 13. Theapparatus of claim 12, wherein the controller is configured to assignthe second operation to the at least one of the plurality of processors,and configured to control the at least one of the plurality ofprocessors to perform the post reconstruction after performing the scanreconstruction.
 14. A method of processing a medical image, the methodcomprising: detecting whether a malfunction occurs among a plurality ofprocessors, each of the plurality of processors being configured to beassigned to one of a first operation having a first priority and asecond operation having a second priority lower than the first priority,to reconstruct a cross-sectional image of an object, and when themalfunction occurs in a processor assigned to the first operation,performing at least one of reassigning the first operation, to theplurality of processors such that a number of the plurality ofprocessors assigned to the first operation is maintained and changinguse rate of the plurality of processors assigned to the first operation.15. The method of claim 14, wherein the changing the use rate comprises:increasing the use rate of the plurality of processors except for theprocessor in which the malfunction is detected.
 16. The method of claim14, wherein the changing the use rate comprises: updating the use ratefor each of the plurality of processors assigned to the first operationand display the use rate for each of the plurality of processors. 17.The method of claim 14, further comprises displaying zero percent of userate for the processor in which the malfunction is detected.
 18. Themethod of claim 14, wherein the reassigning the first operationcomprises: reassigning the second operation, to the plurality ofprocessors such that a number of the plurality of processors assigned tothe second operation is reduced.
 19. The method of claim 14, wherein thereassigning the first operation comprises: updating at least one of theplurality of processors assigned to the first operation; and displayingthe plurality of processors assigned to the first operation.
 20. Acomputer program product comprising a computer readable storage mediumhaving a computer readable program stored therein, wherein the computerreadable program, when executed on a computing device, causes thecomputing device to: detect whether a malfunction occurs among aplurality of processors, each of the plurality of processors beingconfigured to be assigned to one of a first operation having a firstpriority and a second operation having a second priority lower than thefirst priority, to reconstruct a cross-sectional image of an object, andwhen the malfunction occurs in a processor assigned to the firstoperation, perform at least one of reassigning the first operation, tothe plurality of processors such that a number of the plurality ofprocessors assigned to the first operation is maintained and changinguse rate of the plurality of processors assigned to the first operation.